Despite the significant success of the LF representation for constrained face recognition [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]} and expression recognition [9]}, [10]}, this type of visual representation has never been used for face and expression recognition in the wild, where the added value of the LF information may be more critical since the conditions are more extreme and unconstrained.
In this context, this paper proposes to exploit the richer spatio-angular representation acquired with a LF camera, to improve the performance of face and expression recognition systems in the wild. In this paper, ‘in the wild’ refers to facial images captured under several unconstrained acquisition conditions such as random lighting conditions, shading, backgrounds, environments, poses, distances, etc., with minimal or no user cooperation. The key contributions and technical novelty of this paper in the context of LF face and expression recognition in the wild can be described as follows:
